Wind Turbine Collective and Individual Pitch Control Using Quantitative Feedback Theory

Abstract

Individual pitch control is an innovative technique in wind turbine control. It has the potential of reducing the asymmetric mechanical loads on the blades in large multi-megawatt turbines. As the mechanical fatigue is reduced, the lifetime of the turbine can be significantly extended. This work develops an individual pitch control for the National Renewable Energy Laboratory’s (NREL) 5 MW reference wind turbine. The individual pitch controller works along with a collective pitch controller, designed using Quantitative Feedback Theory (QFT) robust control. Simulations of the complete individual and collective pitch control system are conducted with the NREL’s computer-aided engineering tool for horizontal axis wind turbines (FAST). They show that the addition of the individual pitch controller significantly reduces the loads on the tilt and yaw directions in the nacelle and tower of the turbine at 1P and 3P frequencies, and on the blades at the 2P harmonic frequency.

A Comparative Study of Optimal Individual Pitch Control Methods

“…Although PI controllers are primarily used in the industry due to their simplicity and ease of implementation, optimal controllers are found to perform better in reducing rotor speed fluctuations and power variations and simultaneously in load reduction of wind turbines [10][11][12][13]. The H ∞ -based control could suffer from being mathematically complex, being generally of a high order which makes its usage difficult in practical applications [42]. Since a linearised model is taken for the controller design, it can exhibit model-plant mismatch when applied to a real-life turbine [24,30].…”

Machine Learning Control for Floating Offshore Wind Turbine Individual Blade Pitch Control

“…CPC is a conventional paradigm of pitch control that controls the pitch of all the turbine blades with a single pitch command value (Plumley et al 2014). CPC is typically used for the speed regulation set by a central controller, and it has been effective if the wind loading is uniform across the entire rotor (Wheeler and Garcia-Sanz 2017). However, in reality, wind loading across the rotor is unbalanced and constantly changing, which contributes to a significant reduction of turbine blade lifetime (Lu et al 2015).…”

“…IPC is a relatively recent paradigm that aims at controlling individual blade pitches with unique pitch commands to address such unbalanced loadings (Plumley et al 2014). IPC is known to improve speed regulation by supplementing CPCs, as well as increase the blade longevity by reducing unbalanced loads (Wheeler and Garcia-Sanz 2017). Currently, the Coleman transform-based IPC strategy is widely adopted, which is known to be effective under the assumption that the turbine blade dynamics (or its analytical model) can be reasonably approximated via linearization (Lio et al 2017).…”

“…Currently, the Coleman transform-based IPC strategy is widely adopted, which is known to be effective under the assumption that the turbine blade dynamics (or its analytical model) can be reasonably approximated via linearization (Lio et al 2017). The existing works using Coleman transform include those of Wheeler and Garcia-Sanz (2017), Mirzaei et al (2013) (coupled with model predictive control), and Selvam et al (2009) (coupled with linear-quadratic-Gaussian control).…”